Multi-Criteria Decision Based Left-turn Signal Control Guideline

There are primarily three types of left-turn controls at signalized intersections, namely permitted, protected, and protected-permitted. Selecting a left-turn signal control type is one of the major elements in traffic signal design and operations, and should be a systematic approach involving complex decision rules. Existing guidelines for determining the appropriate left-turn signal control has been primarily based on traffic volume, delay, geometry, crash experience, and other related variables. Such existing guidelines are generally presented in a flow-chart format. One of the major shortcomings of the existing guidelines is that a single variable can dominate the decision process, thereby lacking a balanced consideration of all other important variables. This research presents a new guideline for determining left-turn control types mostly applicable for conventional left-turn displays. This research format was developed for a four-leg intersection configuration; however, it can be easily adopted into the other configurations. The guideline is based on the principles of multi-criteria decision analysis and provides an index-based recommendation. This method determines a numerical scale provided a comparison among the three types of left-turn control instead of an absolute left-turn control type. Using the data collected from the field, it shows that the proposed guideline can be calibrated and tailored to specific left-turn control policies of any jurisdiction.

Level thesis:degree_level

Doctorate Degree

Year dc:date.issued

2009

Author dc:creator

• Ozmen, Ozlem

Advisor dc:contributor.advisor

• Tian, Zong Z.

Committee members dc:contributor.committeemember

• Gibby, Adrain R
• Pekcan, Gokhan
• Park, Do-Hawn
• Evrensel, Cahit A

• guidelines
• left turn
• multi-criteria
• signals

Statement dc:rights

• In Copyright(All Rights Reserved)

Handle dc:identifier.uri

http://hdl.handle.net/11714/4191

OAI identifier oai:identifier

oai:scholarwolf.unr.edu:11714/4191